Homomorphic encryption (HE) is a promising technique for privacy-preserving data analysis. Several HE schemes have been developed, with the Cheon-Kim-Kim-Song (CKKS) and Fast Fully Homomorphic Encryption over the Torus (TFHE) schemes being two of the most advanced. However, due to their differences, it is hard to compare their performance and suitability for a given application. We therefore conducted an empirical study of the performance of the two schemes in a comparable scenario. We benchmarked the commonly used operations addition, multiplication, division, square root, evaluation of a polynomial and a comparison function, each on a common pair of datasets with \(2^{16}\) 32-bit integers. Since the CKKS scheme is an approximate scheme, we set a requirement of at least 32 bits of precision to match that of the input data. Our results show that CKKS outperforms TFHE in most operations. TFHE’s only advantage is its fast bootstrapping. Even though TFHE performs bootstrapping after every operation, while CKKS typically performs bootstrapping only after a certain number of multiplications, CKKS’s bootstrapping still presents a bottleneck. This can be seen specifically with the comparison operation, where TFHE is much faster than CKKS in many settings, as it requires several bootstrapping operations in CKKS due to its multiplicative depth. Generally speaking, CKKS should be preferred in applications which can be parallelized. CKKS’s advantages decreases in applications with a large depth that require many bootstrapping operations.